Count 'em: one, two, three new studies on the relationship between IQ and academic achievement in the latest issue of Intelligence (volume 35, issue 1)

Before the studies' precis, a little background on why such studies are necessary. More than anything, such studies are needed because folks such as S. Ceci and R. Sternberg (very prominent and oft-cited) advocate that (traditional) IQ tests are just measuring little more than school related achievement. So, IQ and academic achievement are only related because, for reasons X, Y, and Z (pick your own environmental variables), some folks get more out of school, and it just so happens that the same folks do well on IQ tests due largely (if not entirely) because school achievement and IQ tests are measuring the same thing. Consequently, g is an irrelevant artifact of those damned psychometricians.

An alternative hypothesis (explicated nicely in Jensen1,2), however, is that due largely to genetic factors (which influence both individual differences and environmental influences), people enter school with wide variability in cognitive ability and "readiness to learn." This initial variability then heavily influences (although not completely determines) the amount a given student will pick up as he/she matriculates. As a student gains more information, his/her initial ability and the new information acquired then interact so he/she is able to expand his/her knowledge further, and so on and so forth. Therefore, while one needs access to "information," the child's general cognitive ability is the engine driving his/her educational achievement.

Don't miss the point here. These are two separate, testable, hypotheses. (A) IQ and academic achievement are synonymous. That is, people are smart (or not so smart) almost solely because they had (or did not have) a good education. (B) IQ is independent of academic achievement, although the former significantly influences the latter. That is, you can come from a good school, but not be so bright, and do poorly on achievement tests; likewise, you can come from a school that is not so good, (but meets some very minimum standard), but be bright, and do very well on academic achievement tests.

This study is likely the weakest only because they used a group of college students from an elite university. Not that there is anything wrong with this, but when you see the samples in the studies below, it is a noticeable concern.

Their major contribution was that in predicting (standardized) academic achievement, speed of information processing and spatial ability can explain small, but significant, amounts of variance unexplained by general vocabulary (Mill Hill) and perceptual organization (Raven's Matrices), although the latter two tests, hands down, did the best in predicting academic achievement across various indicators.

This study had 3 advantages over the former: (1) it is longitudinal, (2) the data is from a much wider scope of IQs, and (3) the data comes from all over the US. The drawback, and major caveat, is that the data is all from special education (broadly defined) testing, so the applicability to the entire population is in question. Still, the mean Full Scale IQ score from the WISC-III (the IQ instrument used) is 90 with a SD of 15 (in the general population it is 100 and 15), and the subtest scores hover around 8 with SDs that hover around 3 (in the general population it is 10 and 3).

Because they have longitudinal data on both standardized IQ and standardized achievement tests, they can specifically test the IQ--->Achievement hypothesis (see preamble). What do they find?

This notion of intelligence estimating a student's ability to succeed in school assumes the temporal precedence of intelligence to achievement. . . Regardless, the present study supports the view that intelligence, as measured by the VC [Verbal Comprehension] and PO [Perceptual Organization] dimensions of the WISC-III, influences or is related to future achievement whereas reading and math achievement do not appear to influence or are not related to future psychometric intelligence.

Stated more bluntly:

. . . the present study provides evidence that psychometric intelligence is predictive of future achievement whereas achievement is not predictive of future psychometric intelligence. This temporal precedence is consistent with the theoretical position of Jensen (2000)[1] that intelligence bears a causal relationship to achievement and not the other way around.

Before getting on to the study, a brief word about Dr. Deary. He is the current badass of differential psychology. Because of his background (degrees in medicine and psychology), he is able to investigate psychometric, chronometric, genetic, and neurological aspects (often concurrently) of both intelligence and personality (look at the range on his vita). As if that were not enough, he has challenged the whole field of differential psychology by obtaining multiple population level, longitudinal data sets. So instead of trying to infer from a sample a few hundred to the target population, he is gathering population level samples of thousands of individuals. Case in point:

Deary's study looked at how cognitive ability measured at age 11 predicted academic achievement at age 16. Unsurprisingly, the IQ-Achievement correlations for the Sciences are around .6 (math highest, chemistry lowest), with similar coefficients form Arts/Humanities and Social Studies. Surprisingly, for practical fields (e.g., P.E., Art) the coefficients are a little lower, but not that much, averaging around .5. Here is a pic of the correlation table: (the n is in parentheses; it obviously changes as not every student took every class)

Deary took the analysis a step further however and did a little latent variable modeling. As the IQ test had three components/subtests (verbal, nonverbal, quantitative), he correlated a latent g factor with a latent academic factor using the following subtests: English, English Literature, Math, Science, Geography, French (n=12519). The correlation between the latent factors was .81. That is: 66% of the variance in latent (general) academic achievement can be explained by latent cognitive ability---measured 5 years previously. While he hypothesizes that such things as "school ethos" and "parental support" are good areas to search for the other 34%, based on Rohode's work, it is likely going to be found in residual, first order factors (see Carroll or McGrew).

Take home message: While general cognitive ability and academic achievement are not isomorphic, the former is necessary for the latter, while the converse is not necessarily true. Spearman suggested this more than a century ago, and, to quote the last sentence in Deary's work,

These data establish the validity of g for this important life outcome.

1. Jensen, A. R. (2000, August). The g factor and the design of education. Paper presented at the annual meeting of the American Psychological Association, Washington, DC.